Macroeconomic Announcements and the Distribution of Price-Endings in the U.S. Treasury Market

We investigate how new information impacts quote clustering in the bond market. We find that clustering, along with quote activity, price volatility and bid-ask spreads, increases sharply in the minutes following releases of macroeconomic news. Each returns to near-normal levels within the hour. Effects are strongest for more liquid on-the-run notes and for the announcements typically associated with substantial information flow. The strong positive comovement of clustering, quote activity, price volatility, and bid-ask spreads supports the conclusion that innovations of these variables are endogenous to the arrival and incorporation of information into prices.     

Market Sidedness: Insights into Motives for Trade Initiation

We infer motives for trade initiation from market sidedness. We define trading as more two-sided (one-sided) if the correlation between the number of buyer- and seller-initiated trades increases (decreases), and assess changes in sidedness (relative to a control sample) around events that identify trade initiators. Consistent with asymmetric information, trading is more one-sided before merger news. Consistent with belief heterogeneity, trading is more two-sided before earnings and macro announcements with greater dispersion in analyst forecasts, and after news with larger announcement surprises. We examine the codeterminacy of sidedness, bid-ask spread, volatility, number of trades, and order imbalance.     

Trading Patterns and Prices in the Interbank Foreign Exchange Market

The behavior of quote arrivals and bid-ask spreads is examined for continuously recorded deutsche mark-dollar exchange rate data over time, across locations, and by market participants. A pattern in the intraday spread and intensity of market activity over time is uncovered and related to theories of trading patterns. Models for the conditional mean and variance of returns and bid-ask spreads indicate volatility clustering at high frequencies. The proposition that trading intensity has an independent effect on returns volatility is rejected, but holds for spread volatility. Conditional returns volatility is increasing in the size of the spread.     

When spread bites fast – Volatility and wide bid-ask spread in a mixed high-frequency and low-frequency environment

This research focuses on the impact High-Frequency Trading has on price volatility when bid-ask spread is wide. The theoretical part introduces a set of equations and presents an Agent Based Model implemented via a computer-based simulation. The wide spread leads to the appearance of unusual phenomena caused by the relative speed difference between the fast and slow traders. The latter agents tend to quote limit orders that look irrational, as they are distant more than one tick from the top-of-book. The same relative speed difference causes slow traders to post market orders that execute at price worse than originally intended. Both these abnormal orders tend to increase local volatility. Other results found by the simulation are an increase in global volatility (computed both as the difference of maximum less minimum price and as standard deviation of price distribution) and in volatility at sub-second timescales. These occurrences penalise slower traders and affect market stability. All the results are consistent both under quiet and stressed market conditions. The results found are then compared with audit trail data to verify the soundness of theory against practice.     

Limit order revisions

This paper empirically examines limit order revisions and cancellations which contribute to a significant portion of the order activity in many order-driven markets. We document that limit orders are more likely to be revised or cancelled if they are large and near the bid-ask quote. We show that order revisions generate net economic benefits to traders. Our evidence shows strong links between these activities and limit order submission risk using bid-ask spread, volatility and post-event return as proxies. We also find that these activities are less intense when the opportunity cost to monitor a stock is high, such as during lunch hours or when stock volume relative to the entire market is low.     

Intraday Return Volatility Process: Evidence from NASDAQ Stocks

This paper presents a comprehensive analysis of the distributional and time-series properties of intraday returns. The purpose is to determine whether a GARCH model that allows for time varying variance in a process can adequately represent intraday return volatility. Our primary data set consists of 5-minute returns, trading volumes, and bid-ask spreads during the period January 1, 1999 through March 31, 1999, for a subset of thirty stocks from the NASDAQ 100 Index. Our results indicate that the GARCH(1,1) model best describes the volatility of intraday returns. Current volatility can be explained by past volatility that tends to persist over time. These results are consistent with those of Akgiray (1989) who estimates volatility using the various ARCH and GARCH specifications and finds the GARCH(1,1) model performs the best. We add volume as an additional explanatory variable in the GARCH model to examine if volume can capture the GARCH effects. Consistent with results of Najand and Yung (1991) and Foster (1995) and contrary to those of Lamoureux and Lastrapes (1990), our results show that the persistence in volatility remains in intraday return series even after volume is included in the model as an explanatory variable. We then substitute bid-ask spread for volume in the conditional volatility equation to examine if the latter can capture the GARCH effects. The results show that the GARCH effects remain strongly significant for many of the securities after the introduction of bid-ask spread. Consistent with results of Antoniou, Homes and Priestley (1998), intraday returns also exhibit significant asymmetric responses of volatility to flow of information into the market.     

VOLATILITY AND LIQUIDITY AT NYSE OPENING CALLS: A CLOSER LOOK

The literature suggests that the bid-ask spread is responsible, at least in part, for greater price volatility and more negative autocorrelation at the open than at the close. In this study, we find that these phenomena are not related to the bid-ask spread, but are related instead to pricing errors by specialists or limit-order traders around the open. We use George, Kaul, and Nimalendran's (1991) model, which is less biased than Roll's (1984) model, to estimate the implied spread. The results show that, on average, the implied spread earned by liquidity suppliers is lower at the open than at the close. These results refute the contention that specialists exploit their monopoly position and earn a higher profit at the opening call. The evidence is consistent with the hypothesis that specialists set a lower cost of immediacy to encourage trading and the release of more information at the opening call. This could reduce information asymmetry and make subsequent trades in the continuous market more profitable.     

国外高频交易的发展现状及启示

证券市场上的高频交易模式大体上分为四类:订单拆分策略、做市交易策略、定量化交易策略和其他策略。研究发现:(1)高频交易降低了买卖价差,提高了市场流动性,而并没有增加市场波动率,甚至反而可能降低了市场波动率;(2)没有发现高频交易者存在系统性抢单行为(并不排除有特定高频交易者存在此类行为);(3)学术研究认为高频交易有导致市场风险的可能性,但是事件调查大多认为高频交易不是引发市场风险的罪魁祸首。本文认为,对高频交易的监管应该注重抓住重点区别对待,以维护公平、透明、高效的市场秩序。     

EMPIRICAL EVIDENCE ON THE IMPACT OF THE BID-ASK SPREAD ON THE CHARACTERISTICS OF CRSP DAILY RETURNS

It is widely recognized that Center for Research in Security Prices (CRSP) returns may differ from “true” returns because of the bid-ask effect. Using a large sample of New York Stock Exchange and American Stock Exchange securities, I confirm a discernible bid-ask effect, the magnitude and importance of which decrease with the security's price level (increase with the spread). I find volatility estimates using CRSP returns to be greater than those based on quote returns. However, market model properties, such as β and R², are generally unaffected. Bid-ask effects are clearly apparent in event studies, but because of certain offsetting effects commonly used test statistics remain unaffected. Low-priced stocks (below $2.00) do not conform to these patterns. Finally, the evidence raises the possibility that the existing literature on filter rule tests may underestimate the bid-ask spread component of transaction costs.     

Does high-frequency trading actually improve market liquidity? A comparative study for selected models and measures

The increasing volume of messages sent to the exchange by algorithmic traders stimulates a fierce debate among academics and practitioners on the impacts of high-frequency trading (HFT) on capital markets. By comparing a variety of regression models that associate various measures of market liquidity with measures of high-frequency activity on the same dataset, we find that for some models the increase in high-frequency activity improves market liquidity, but for others, we get the opposite effect. We indicate that this ambiguity does not depend only on the stock market or the data period, but also on the used HFT measure: the increase of high-frequency orders leads to lower market liquidity whereas the increase in high-frequency trades improves liquidity. We hypothesize that the observed decrease in market liquidity associated with an increasing level of high-frequency orders is caused by a rise in quote volatility.     

Why do security prices change? A transaction-level analysis of NYSE stocks

This article develops and tests a structural model of intradayprice formation that embodies public information shocks andmicrostructure effects. We use the model to analyze intradaypatterns in bid-ask spreads, price volatility, transaction costs,and return and quote auto-correlations, and to construct metricsfor price discovery and effective trading costs. Informationasymmetry and uncertainty over fundamentals decrease over theday, although transaction costs increase. The results help explainthe U-shaped pattern in intraday bid-ask spreads and volatility,and are also consistent with the intra-day decline in the varianceof ask price changes.     

Market structure and microstructure, in international interest rate futures markets

We examine the role of market structure in identifying microstructure features of the NYSE.Euronext-LIFFE STIR futures market by comparing the ability of two bid-ask spread component models to explain bid-ask spreads. These two models differ only in their assumptions about whether or not market makers are present. The period we analyze includes data from pit-based trading alongside electronic market data. We explore how market structure affects the way private information influences bid-ask spreads and return volatility. A second part of our study employs intraday correlation to investigate these links in greater depth, while a third part looks at how private information and trading noise contribute to price evolution.     

Forecasting volatility of the U.S. oil market

We examine the information content of the CBOE Crude Oil Volatility Index (OVX) when forecasting realized volatility in the WTI futures market. Additionally, we study whether other market variables, such as volume, open interest, daily returns, bid-ask spread and the slope of the futures curve, contain predictive power beyond what is embedded in the implied volatility. In out-of-sample forecasting we find that econometric models based on realized volatility can be improved by including implied volatility and other variables. Our results show that including implied volatility significantly improves daily and weekly volatility forecasts; however, including other market variables significantly improves daily, weekly and monthly volatility forecasts.     

AN IMPLICIT MEASURE OF THE EFFECTIVE BID-ASK SPREAD: A NOTE

We extend Roll's study of the effective bid-ask spread in an efficient market environment by allowing for serially correlated order arrival and quote behavior. This extension results in a more general effective bid-ask spread measure, which precludes imaginary spreads and includes Roll's measure as a special case when the serial correlation is zero. This new measure is related to the length of the measurement interval due to the serial correlation, and thus has the potential to explain the previously observed differential between weekly and daily derived spreads.     

THE DEALERS' PRICE/SIZE QUOTE AND MARKET LIQUIDITY

We model trading in a competitive securities market where informed traders and liquidity traders transact with dealers. The dealers' entire published quote is modeled: bid-ask prices and the number of shares the dealer is willing to buy/sell at these prices (i.e., size quotes). We argue that size quotes are a more informative indicator of market liquidity than the bid-ask spread's adverse-selection component. Moreover, the size quotes reveal several market characteristics that cannot be inferred from the bid-ask spread's adverse-selection component alone. The model generates a number of empirically testable predictions that clarify certain key elements of market liquidity.     

柜台市场会计信息披露研究——国外文献述评与启示

会计信息披露是降低信息不对称的重要方式,柜台市场信息的不对称影响做市商的报价价差,从而影响市场的流动性。本文分别围绕会计信息披露对买卖价差的影响、会计信息披露对市场流动性的影响、会计信息披露与柜台市场有效性的关系三方面,对国外文献进行梳理和分析,并阐明会计信息披露对构建我国柜台市场的重要意义。     

FX spreads and dealer competition across the 24-hour trading day

This study examines the impact of competition on bid-ask spreadsin the spot foreign exchange market. We measure competitionprimarily by the number of dealers active in the market andfind that bid-ask spreads decrease with an increase in competition,even after controlling for the effects of volatility. The expectedlevel of competition is time varying, highly predictable, anddisplays a strong seasonal component that in part is inducedby geographic concentration of business activity over the 24-hourtrading day. Our estimates show that the expected addition ofone more competing dealer lowers the average quoted spread by1.7%     

High-Frequency Trading and Market Performance

We study the consequences of, and potential policy responses to, high-frequency trading (HFT) via the tradeoff between liquidity and information production. Faster speeds facilitate HFT, with consequences for this tradeoff: Information production decreases because informed traders have less time to trade before HFTs react, but liquidity (measured by the bid-ask spread) improves because informational asymmetries decline. HFT also pushes outcomes inside the frontier of this tradeoff. However, outcomes can be restored to the frontier by replacing the limit order book with one of two alternative mechanisms: delaying all orders except cancellations or implementing frequent batch auctions.     

Currency bid-ask spread dynamics and the Asian crisis: Evidence across currency regimes

Using a sample of 21 emerging and developed country currencies, we evaluate the impact of the Asian crisis on bid-ask spreads. While the crisis had widespread and uniform volatility effects, the spread effects were not uniform across emerging and developed country currencies. For Asian emerging markets, spreads widened and spread volatility increased significantly during the crisis, while developed markets spreads narrowed and spread volatility decreased significantly. We investigate the impact of more flexible and less flexible exchange rate regimes on bid-ask spreads using panel data. In general, countries with tightly-managed regimes have significantly lower spreads than countries with more freely-floating regimes, while controlling for the influence of other factors such as volatility. Asian developing market spreads are higher than spreads of the other countries, again, after controlling for the influence of other factors.     

Asymmetric information and the bid-ask spread: an empirical comparison between automated order execution and open outcry auction

This study examines the components of the bid-ask spread on the Sydney Futures Exchange. The Exchange uses open outcry auction for daytime trading, and switches to a screen-based automated order execution system at 16:30 h for overnight trading. After controlling for proxies of order flow characteristics, the study finds that screen-based traders are more sensitive to market volatility than floor-based traders in setting the bid-ask spread. Spreads from floor trading have a smaller adverse information component but a larger order processing cost component relative to screen trading. The results suggest that floor traders can better assess the presence of adverse information than screen traders.